Patient attitudes towards the arteriovenous fistula: a qualitative study on vascular access decision making
Bibliographic record
Abstract
BACKGROUND: The use of arteriovenous fistulas (AVFs) among hemodialysis (HD) patients has been consistently associated with lower rates of morbidity and mortality; however, up to 30% of eligible patients refuse the creation or cannulation of an AVF. We aimed to understand the attitudes, beliefs, preferences and values of patients who refused creation or use of an AVF. METHODS: With qualitative methodology, we conducted semi-structured interviews with 13 HD patients (Canada, 2009), who previously refused creation or use of an AVF. Three independent analysts reviewed interview transcripts. RESULTS: We discovered three main themes that impacted the decision to refuse a fistula: (i) poor previous personal or vicarious experiences with the fistula, including cannulation, bleeding, time commitment and appearance; (ii) knowledge transfer and informed decision making. Patients identified information from other patients to be as important as information from health care workers, that information on vascular access (VA) was presented but not understood and that timing of information was crucial with information overload at the start of dialysis and (iii) maintenance of status quo and outlook on life. Some patients stated they live day-to-day without being influenced by the mortality risks with a catheter. CONCLUSIONS: AVF refusal is multifactorial and depends on individual patients. Although nephrologists consider the fistula to be the optimal VA, patients do not think in the same terms of reducing infection rates but focus on the practical day-to-day use of their VA and its influence on their quality of life and future outlook.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".